Transfer learning for named-entity recognition with neural networks
Recent approaches based on artificial neural networks (ANNs) have shown promising results for named-entity recognition (NER). In order to achieve high performances, ANNs need to be trained on a large labeled dataset. However, labels might be difficult to obtain for the dataset on which the user want...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
European Language Resources Association
2020
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| Online Access: | https://hdl.handle.net/1721.1/123340 |